Abstract
The simulation of subtractive manufacturing processes has a long history in engineering. Corresponding predictions are utilized for planning, validation and optimization, e.g., of CNC-machining processes. With the up-rise of flexible robotic machining and the advancements of computational and algorithmic capability, the simulation of the coupled machine-process behaviour for complex machining processes and large workpieces is within reach. These simulations require fast material removal predictions and analysis with high spatial resolution for multi-axis operations. Within this contribution, we propose to leverage voxel-based concepts introduced in the computer graphics industry to accelerate material removal simulations. Corresponding schemes are well suited for massive parallelization. By leveraging the computational power offered by modern graphics hardware, the computational performance of high spatial accuracy volumetric voxel-based algorithms is further improved. They now allow for very fast and accurate volume removal simulation and analysis of machining processes. Within this paper, a detailed description of the data structures and algorithms is provided along a detailed benchmark for common machining operations.
Highlights
Simulation of material removal processes is a wellestablished practice in industry
We demonstrate a novel concept for geometric material removal simulation and analysis, which allows for a fast and accurate prediction of the tool engagement and the process forces as a key enabler for industrialization of robotic machining, especially for large workpieces
The presented voxel-based approach allows for the representation of large work pieces without impairing the spatial accuracy of the in-process work piece. This property allows for the simulation of the machining of large work pieces typically manufactured by robotic machining systems
Summary
We demonstrate a novel concept for geometric material removal simulation and analysis, which allows for a fast and accurate prediction of the tool engagement and the process forces as a key enabler for industrialization of robotic machining, especially for large workpieces. The concept leverages recent advancements of voxel-based modelling on Graphic Processing Units (GPUs) [28] for the simulation of the material removal and the prediction of the engagement between the tool and the workpiece. Based on the geometric predictions, process forces can be calculated accurately using mechanistic process force models. By adopting the technology for machine tool design, milling operation planning, and feed. Int J Adv Manuf Technol (2021) 115:275–289 forward displacement compensation, a paradigm shift from rigidly designed machines to intelligent machine tools that adapt to expected process forces and performance criteria could be achieved. Besides the use case of process force prediction, highly efficient and modifiable volumetric models with a high spatial resolution, a low memory footprint, efficient data structures, and data modification algorithms can be utilized in other areas like simulated surgery, process simulation for additive manufacturing, and simulation of modifiable environments
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